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The rapid development of sequencing technologies over the last decades brought molecular genetics close to its medical applications. However, genome-based personalized medicine is still in its early age as its implementation requires reliable tools for annotating and interpreting individual genome variants, including widespread single-nucleotide variants (SNVs).
In this study, we utilized the cap analysis of gene expression (CAGE) data to construct an atlas of transcribed regulatory elements of diverse human skeletal muscles and assess the functional effect of SNVs by estimating the allelic imbalance in the transcriptional activity of promoters and enhancers.
As a result, we identified more than 20 thousand CAGE clusters, including more than 1.5 thousand bidirectional enhancers. More than 3/4 of promoters and enhancers exhibited tissue-specific activity across different skeletal muscles, highlighting very specific gene expression patterns in eye, tongue, and diaphragm. Next, we performed the SNV calling which yielded more than 15 thousand reliable variants and detected more than 6 thousand allele-specific events with a significant allelic imbalance in at least one skeletal muscle type.
We believe that our work will be useful for studying gene expression patterns and variant effects in healthy muscles as well as myopathies.